Difference between Greedy Approach and Dynamic Programming
Feature | Greedy Approach | Dynamic Programming |
---|---|---|
Optimality | May not always provide an optimal solution. | Guarantees an optimal solution if the problem exhibits the principle of optimality. |
Subproblem Reuse | Does not reuse solutions to subproblems. | Reuses solutions to overlapping subproblems. |
Backtracking | Does not involve backtracking. | May involve backtracking, especially in top-down implementations. |
Complexity | Typically simpler and faster to implement. | May be more complex and slower to implement. |
Application | Suitable for problems where local optimization leads to global optimization. | Suitable for problems with overlapping subproblems and optimal substructure. |
Examples | Minimum Spanning Tree, Shortest Path algorithms. | Fibonacci sequence, Longest Common Subsequence. |
Related Articles:
- Greedy Algorithm
- Dynamic programming
- Optimal substructure
- Overlapping subproblem
Greedy Approach vs Dynamic programming
Greedy approach and Dynamic programming are two different algorithmic approaches that can be used to solve optimization problems. Here are the main differences between these two approaches: